Search

BACKGROUND: Numerous studies have linked fine particulate matter (PM2.5) to increased cardiovascular mortality. Less is known how the PM2.5-cardiovascular mortality association varies by use of cardiovascular medications. This study sought to quantify effect modification by statin use status on the associations between long-term exposure to PM2.5 and mortality from any cardiovascular cause, coronary heart disease (CHD), and stroke. METHODS: In this nested case-control study, we followed 1.2 million community-dwelling adults aged ≥66 years who lived in Ontario, Canada from 2000 through 2018. Cases were patients who died from the three causes. Each case was individually matched to up to 30 randomly selected controls using incidence density sampling. Conditional logistic regression models were used to estimate odds ratios (ORs) for the associations between PM2.5 and mortality. We evaluated the presence of effect modification considering both multiplicative (ratio of ORs) and additive scales (the relative excess risk due to interaction, RERI). RESULTS: Exposure to PM2.5 increased the risks for cardiovascular, CHD, and stroke mortality. For all three causes of death, compared with statin users, stronger PM2.5-mortality associations were observed among non-users [e.g. for cardiovascular mortality corresponding to each interquartile range increase in PM2.5, OR = 1.042 (95% CI, 1.032-1.053) vs OR = 1.009 (95% CI, 0.996-1.022) in users, ratio of ORs = 1.033 (95% CI, 1.019-1.047), RERI = 0.039 (95% CI, 0.025-0.050)]. Among users, partially adherent users exhibited a higher risk of PM2.5-associated mortality than fully adherent users. CONCLUSIONS: The associations of chronic exposure to PM2.5 with cardiovascular and CHD mortality were stronger among statin non-users compared to users.

Emissions of fine particulate matter (PM2.5) from human activities have been linked to substantial disease burdens, but evidence regarding how reducing PM2.5 at its sources would improve public health is sparse. We followed a population-based cohort of 2.7 million adults across Canada from 2007 through 2016. For each participant, we estimated annual mean concentrations of PM2.5 and the fractional contributions to PM2.5 from the five leading anthropogenic sources at their residential address using satellite observations in combination with a global atmospheric chemistry transport model. For each source, we estimated the causal effects of six hypothetical interventions on 10-y nonaccidental mortality risk using the parametric g-formula, a structural causal model. We conducted stratified analyses by age, sex, and income. This cohort would have experienced tangible health gains had contributions to PM2.5 from any of the five sources been reduced. Compared with no intervention, a 10% annual reduction in PM2.5 contributions from transportation and power generation, Canada's largest and fifth-largest anthropogenic sources, would have prevented approximately 175 (95%CI: 123-226) and 90 (95%CI: 63-117) deaths per million by 2016, respectively. A more intensive 50% reduction per year in PM2.5 contributions from the two sources would have averted 360 and 185 deaths per million, respectively, by 2016. The potential health benefits were greater among men, older adults, and low-income earners. In Canada, where PM2.5 levels are among the lowest worldwide, reducing PM2.5 contributions from anthropogenic sources by as little as 10% annually would yield meaningful health gains.

Background Long-term exposure to outdoor fine particulate matter (PM2.5) is the leading environmental risk factor for premature mortality worldwide. Characterizing important pathways through which PM2.5 increases individuals' mortality risk can clarify the PM2.5-mortality relationship and identify possible points of interventions. Recent evidence has linked PM2.5 to the onset of diabetes and cardiovascular disease, but to what extent these associations contribute to the effect of PM2.5 on mortality remains poorly understood. Methods and Results We conducted a population-based cohort study to investigate how the effect of PM2.5 on nonaccidental mortality is mediated by its impacts on incident diabetes, acute myocardial infarction, and stroke. Our study population comprised ≈200 000 individuals aged 20 to 90 years who participated in population-based health surveys in Ontario, Canada, from 1996 to 2014. Follow-up extended until December 2017. Using causal mediation analyses with Aalen additive hazards models, we decomposed the total effect of PM2.5 on mortality into a direct effect and several path-specific indirect effects mediated by diabetes, each cardiovascular event, or both combined. A series of sensitivity analyses were also conducted. After adjusting for various individual- and neighborhood-level covariates, we estimated that for every 1000 adults, each 10 μg/m3 increase in PM2.5 was associated with ≈2 incident cases of diabetes, ≈1 major cardiovascular event (acute myocardial infarction and stroke combined), and ≈2 deaths annually. Among PM2.5-related deaths, 31.7% (95% CI, 17.2%-53.2%) were attributable to diabetes and major cardiovascular events in relation to PM2.5. Specifically, 4.5% were explained by PM2.5-induced diabetes, 22.8% by PM2.5-induced major cardiovascular events, and 4.5% through their interaction. Conclusions This study suggests that a significant portion of the estimated effect of long-term exposure to PM2.5 on deaths can be attributed to its effect on diabetes and cardiovascular diseases, highlighting the significance of PM2.5 on deteriorating cardiovascular health. Our findings should raise awareness among professionals that improving metabolic and cardiovascular health may reduce mortality burden in areas with higher exposure to air pollution.

The purpose of this study is to examine the debt burdens, perceived capabilities, and mental health of young adults. Panel data constructed from the 2009 to 2013 waves of the Panel Study of Income Dynamics (PSID) and its Transition to Adulthood (TA) supplement are used in this study. The multinomial logistic regression analysis findings showed that the amount of revolving debt was negatively associated with young adults' mental health. On the other hand, perceived abilities in acting responsibly, in solving problems, and in managing money were positively associated with the mental health of young adults. The fixed effects regression analysis results indicate that the amounts of credit card and student loan debt from the previous period were negatively associated with an increase in the mental health continuum scores of young adults over time. A discussion of the implications of this study's key findings for scholars, policymakers, and practitioners is included.

A growing number of educators expect that artificial intelligence (AI) will augment students' capacities and rapidly transform the teaching and learning practice. However, there is a lack of convincing evidence on the effects of Student-AI Collaboration (SAC) on a learning task's performance. A critical examination of the effects on students' learning performance is a crucial step in understanding the potential benefits of SAC on learning. Through a repeated measure experiment participated by 20 undergraduate students in South Korea, this study examined the effects of SAC on a public advertisement drawing task. The findings revealed that SAC significantly affects creativity in content, expressivity in expression, and public utility in effectiveness varied depending on students' attitude toward AI or on the level of drawing skill. Implications for the design of educational AI and AI literacy education are discussed.

This study employs critical ethnographic child-parent research to examine Korean American children's lived experiences related to anti-Asian racism, looking closely at children's ordinary interactions in their everyday lives at home. Children's conversations at home were audio- and video-recorded and artifacts created by children and from school were collected. While children as co-researchers actively participated in the research, they shared their perspectives on race and anti-Asian racism, noticing the invisibility and stereotypes of Asian Americans. The children's counterstories from child-parent research reveal that racialized discourses toward Asians and Asian Americans are not discussed at school even though children experience them. This study opens more conversations to understand and navigate Asian American children's perspectives on race and racism and methodological insights for racially minoritized parent research with children.

BackgroundThe tremendous global health burden related to COVID-19 means that identifying determinants of COVID-19 severity is important for prevention and intervention. We aimed to explore long-term exposure to ambient air pollution as a potential contributor to COVID-19 severity, given its known impact on the respiratory system.MethodsWe used a cohort of all people with confirmed SARS-CoV-2 infection, aged 20 years and older and not residing in a long-term care facility in Ontario, Canada, during 2020. We evaluated the association between long-term exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2) and ground-level ozone (O3), and risk of COVID-19-related hospital admission, intensive care unit (ICU) admission and death. We ascertained individuals' long-term exposures to each air pollutant based on their residence from 2015 to 2019. We used logistic regression and adjusted for confounders and selection bias using various individual and contextual covariates obtained through data linkage.ResultsAmong the 151 105 people with confirmed SARS-CoV-2 infection in Ontario in 2020, we observed 8630 hospital admissions, 1912 ICU admissions and 2137 deaths related to COVID-19. For each interquartile range increase in exposure to PM2.5 (1.70 μg/m3), we estimated odds ratios of 1.06 (95% confidence interval [CI] 1.01-1.12), 1.09 (95% CI 0.98-1.21) and 1.00 (95% CI 0.90-1.11) for hospital admission, ICU admission and death, respectively. Estimates were smaller for NO2. We also estimated odds ratios of 1.15 (95% CI 1.06-1.23), 1.30 (95% CI 1.12-1.50) and 1.18 (95% CI 1.02-1.36) per interquartile range increase of 5.14 ppb in O3 for hospital admission, ICU admission and death, respectively.InterpretationChronic exposure to air pollution may contribute to severe outcomes after SARS-CoV-2 infection, particularly exposure to O3.

In spite of the increased attention that has been given to early critical literacy practices, there remains a limited amount of scholarship dedicated to exploring how critical literacy may be implemented in early childhood classrooms to prevent bullying. As such, the purpose of this article is to examine the pedagogical potential of early critical literacy with bullying-themes, for educating young children on anti-bullying. Using a qualitative study approach, this study was conducted in a classroom of twenty 5-year-old children in a metropolitan city in South Korea. The central focus of this study was dedicated to examining how children's understanding of bullying toward their peers of different racial/ethnic backgrounds and special needs change through a series of critical literacy activities, including reading, discussion, and follow-up role-playing and writing activities. Findings suggest that critical literacy activities on bullying have the potential to aid in creating anti-bullying environments in which young children critically examine bullying issues from multiple perspectives and actively generate their own understanding of bullying.

Preparing students to collaborate with AI remains a challenging goal. As AI technologies are new to K-12 schools, there is a lack of studies that inform how to design learning when AI is introduced as a collaborative learning agent to classrooms. The present study, therefore, aimed to explore teachers' perspectives on what: (1) curriculum design, (2) student-AI interaction, and (3) learning environments are required to design student-AI collaboration (SAC) in learning and (4) how SAC would evolve. Through in-depth interviews with 10 Korean leading teachers in AI in Education (AIED), the study found that teachers perceived capacity and subject-matter knowledge building as the optimal learning goals for SAC. SAC can be facilitated through interdisciplinary learning, authentic problem solving, and creative tasks in tandem with process-oriented assessment and collaboration performance assessment. While teachers expressed instruction on AI principles, data literacy, error analysis, AI ethics, and AI experiences in daily life were crucial support, AI needs to offer an instructional scaffolding and possess attributes as a learning mate to enhance student-AI interaction. In addition, teachers highlighted systematic AIED policy, flexible school system, the culture of collaborative learning, and a safe to fail environment are significant. Teachers further anticipated students would develop collaboration with AI through three stages: (1) learn about AI, (2) learn from AI, and (3) learn together. These findings can provide a more holistic understanding of the AIED and implications for the educational policies, educational AI design as well as instructional design that are aimed at enhancing SAC in learning.

To scale up pedagogical innovation using information and communications technology (ICT), educators have shifted the focus of professional development from primarily an individualist endeavor to a collective approach including teachers' social networks (SNs). SNs have been found to be a major contributor to professional development and support, which in turn promote teachers' self-efficacy and improve their teaching practices. However, the effects of SNs in pedagogical innovation may vary depending on the structure of SNs and the quality of the interaction in a network. It is necessary to reconsider the assumption that the more networked teachers become, the better they teach students. This study aims to explore both the supportive and obstructive roles of teachers' SNs in scaling up ICT-based instruction through in-depth interviews with 14 primary school teachers (7 active and 7 passive ICT using teachers) in South Korea. This study found that some SNs played a positive role in supporting ICT-based instruction and professional development, whereas some imposed constraints on using ICT for teaching and learning. Teachers who actively conducted ICT-based instruction were likely to have appropriate countermeasures to obstructive SNs. This study suggests that systematic supports are necessary to help teachers expand their supportive SNs in and out of schools and to develop professional competencies to overcome the negative impacts of obstructive SNs.

For scaling up pedagogical innovation with information and communications technology (ICT), governments around the world put a concerted effort into teachers' acceptance of ICTs and the actual use of ICTs for instruction, yet there is limited literature about the conceptual framework of teachers accepting the ICTs and their usage for instruction typically in the Asia-Pacific region. To fill such gaps in the current literature, this study aims to construct a conceptual model of teachers' effective practice of ICT-based instruction under a mandatory context in the Philippines based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Through a survey conducted by 305 secondary school teachers in the Philippines, this study revealed that performance expectancy (PE), effort expectancy (EE), social influence (SI) and education policy (EP) have significant effects on teachers' behavioural intention to use ICTs (BI) and BI, teachers' ICTs use habit (IUH) and facilitating conditions (FCs) have positive effects on the actual use of ICTs for instruction. The study then recommends a series of actions to improve research and policy on teachers' use of ICT-based instruction.